Field of the Invention
The present invention relates generally to browsing through collections of visual subject matter and, more specifically, to image selection using automatically generated semantic metadata.
Description of the Related Art
The ever-increasing use of digital imaging has made the storage and dissemination of visual subject matter, such as images and videos, very convenient for the average user. However, searching through large-scale digital collections for a particular image or video can be time-consuming, inconvenient, or both. This is because visual subject matter that has not been tagged in some way with easily remembered metadata can generally only be found by browsing through a very large number of images, even when filtering algorithms are used to narrow the search. Typically, automatically assigned metadata, such as the date and time that the desired image or video was created, are rarely useful in facilitating a user's search. Similarly, metadata tags that are manually assigned to individual images and videos by a user have limited value, such as subject matter categories, descriptions, and/or titles, since efficient searching requires a user to remember what tag or tags were assigned to a desired image long after the image was originally downloaded or created. For a collection of visual subject matter that includes hundreds of videos and images that may be organized into dozens of manually assigned categories, relying on user memory as the primary instrument for finding a particular item is unrealistic and unreliable.
As the foregoing illustrates, there is a need in the art for a more effective way to search for visual subject matter stored in a database.